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ERIC Number: ED560419
Record Type: Non-Journal
Publication Date: 2013
Pages: 144
Abstractor: As Provided
Reference Count: N/A
ISBN: 978-1-3033-8970-2
An Evaluation of a Computer-Based Training on the Visual Analysis of Single-Subject Data
Snyder, Katie
ProQuest LLC, Ph.D. Dissertation, Utah State University.
Visual analysis is the primary method of analyzing data in single-subject methodology, which is the predominant research method used in the fields of applied behavior analysis and special education. Previous research on the reliability of visual analysis suggests that judges often disagree about what constitutes an intervention effect. Considering that visual analysis involves a complex set of discriminations and sometimes produces disagreement among experts, it is particularly important to examine methods to train individuals to visually analyze data. Only a handful of studies have investigated the effectiveness of trainings on visual analysis. Most have relied on mechanical methods and/or evaluated the effectiveness of the procedure using a narrow set of graphs (e.g., graphs without slope). The purpose of this study was to evaluate two training methods using graphs with various combinations of effect types. The computer-based training, which includes high rates of practice with feedback, was compared to a lecture condition and a control condition. Results indicate that both training methods (i.e., the computer-based training and the lecture) were more effective than a control condition, but were not substantially different from one another. We discuss the implications of these results for training individuals in visual analysis as well as directions for future research. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page:]
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site:
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A